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Augmented Harris Hawks Optimizer with Gradient-Based-Like Optimization: Inverse Design of All-Dielectric

Kofi Edee1

  • 1Université Clermont Auvergne, Clermont Auvergne INP, CNRS, Institut Pascal, F-63000 Clermont-Ferrand, France.

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Summary
This summary is machine-generated.

A new hybrid optimization method, Gradient-Based-Like Harris Hawks Optimizer (GBL-HHO), improves metasurface inverse design by combining gradient-based and Harris Hawks optimization. This approach efficiently finds optimal metasurface designs, outperforming the original Harris Hawks Optimizer.

Keywords:
inverse designmetasurfacesoptimization

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Area of Science:

  • Computational electromagnetics and materials science.
  • Metasurface inverse design and optimization algorithms.

Background:

  • Metasurfaces offer unique electromagnetic properties but require sophisticated inverse design methods.
  • Population-based algorithms like Harris Hawks Optimizer (HHO) can struggle with local optima in complex design spaces.
  • Gradient-based methods offer efficiency but are sensitive to initial conditions.

Purpose of the Study:

  • To develop a hybrid optimization method for efficient inverse design of metasurfaces.
  • To overcome the limitations of the original Harris Hawks Optimizer (HHO) in the exploitation phase.
  • To leverage the strengths of gradient-based-like (GBL) methods and HHO for improved global optimum searching.

Main Methods:

  • Introduction of a hybrid Gradient-Based-Like Harris Hawks Optimizer (GBL-HHO).
  • Pre-selection of initial candidates using a GBL optimization method.
  • Integration of GBL's broad design space exploration with HHO's population-based search.

Main Results:

  • The GBL-HHO method demonstrates superior performance compared to the original HHO.
  • The hybrid approach efficiently targets a class of unseen global optimal solutions.
  • Successful application in designing all-dielectric meta-gratings for wave deflection.

Conclusions:

  • The proposed GBL-HHO hybrid optimization is an effective strategy for metasurface inverse design.
  • This method enhances the efficiency and accuracy of finding optimal metasurface structures.
  • The findings present a significant advancement in computational design of electromagnetic devices.